Embodiments of the present specification relate to imaging, and more particularly to the detection of motion in dynamic medical images.
In modern healthcare facilities, non-invasive imaging systems are often used for identifying, diagnosing, and treating physical conditions. Medical imaging encompasses different non-invasive techniques used to image and visualize the internal structures and/or functional behavior (such as chemical or metabolic activity) of organs and tissues within a patient. Currently, a number of modalities of medical diagnostic and imaging systems exist, each typically operating on different physical principles to generate different types of images and information. These modalities include ultrasound systems, computed tomography (CT) systems, X-ray systems (including both conventional and digital or digitized imaging systems), positron emission tomography (PET) systems, single photon emission computed tomography (SPECT) systems, and magnetic resonance (MR) imaging systems.
In clinical practice, currently, two-dimensional (2D) medical images, three-dimensional (3D) medical images, and/or four-dimensional (4D) medical images are being routinely used for tracking contrast uptake, delivery of dose and to study time related variations of anatomy and physiology. Specifically, in Dynamic Contrast Enhanced MRI (DCE-MRI), the uptake of contrast is analyzed for understanding the perfusion characteristics and cell structure, which may be indicative of tumor properties.
As will be appreciated, the 4D acquisitions typically entail long scan times for the complete scan. By way of example, acquiring data during 4D magnetic resonance imaging (MRI) generally calls for scan times that run into several minutes. Furthermore, during such long scans, patients under observation may experience voluntary and/or involuntary motion. Patient motion is one of the major challenges in the interpretation of image data. Particularly, patient motion hampers and/or distorts the quality of acquisition of image data. Some examples of patient motion during a scan may include a rapid shift, which may be caused due to the patient coughing or sneezing, motion due to breathing, and the like. Additionally, patient discomfort during the scan may also result in poor quality of data acquisition.
It may therefore be desirable to detect the presence of any patient motion during the acquisition of image data. The detection of motion may in turn be employed to aid in determining a corrective course of action. More particularly, clinical workflow may be greatly enhanced if information regarding the detected motion and a quantification of the detected motion is provided to a clinician during the acquisition of the image data.
Early efforts for detecting patient motion during the scan procedure include use of feature based methods. Other currently existing techniques entail use of registration methods for detecting and correcting patient motion. However, the currently available methods for detecting and correcting patient motion tend to be computationally very intensive and time consuming. Additionally, use of these techniques may entail user intervention or call for a trained clinician.
Furthermore, certain techniques for the acquisition of image data entail use of a contrast agent. However, use of the contrast agent may adversely affect the detection of motion as uptake of the contrast agent may confound visual perception of motion. In addition, detection and correction of motion using the currently available techniques in the presence of contrast changes during the dynamic acquisition is a challenging task.